Intelligent learning environment: Difference between revisions
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== Definition == | == Definition == | ||
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'''Intelligent learning environments''' are based on various combinations of principles from [[microworld]]s, [[intelligent tutoring system]]s, [[cognitive tool]]s and [[CSCL]]. | '''Intelligent learning environments''' are based on various combinations of principles from [[microworld]]s, [[intelligent tutoring system]]s, [[cognitive tool]]s and [[CSCL]]. | ||
Dillenbourg et al. ([http://tecfa.unige.ch/tecfa/research/memolab/report93-chap1.html]) offer this definition | |||
{{quotationbox | The term `intelligent learning environment' (ILE) refers to a category of educational software in which the learner is `put' into a problem solving situation. A learning environment is quite different from traditional courseware based on a sequence of questions, answers and feedback. The best known example of a learning environment is a flight simulator: the learner does not answer questions about how to pilot an aircraft, he learns how to behave like a "real" pilot in a rich flying context... | {{quotationbox | The term `intelligent learning environment' (ILE) refers to a category of educational software in which the learner is `put' into a problem solving situation. A learning environment is quite different from traditional courseware based on a sequence of questions, answers and feedback. The best known example of a learning environment is a flight simulator: the learner does not answer questions about how to pilot an aircraft, he learns how to behave like a "real" pilot in a rich flying context... | ||
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# a problem solving situation ''and'' | # a problem solving situation ''and'' | ||
# one or more agents that assist the learner in his task and monitor his learning.}} | # one or more agents that assist the learner in his task and monitor his learning.}} | ||
Other views (Brusilovsky, 2004, Kay, 1997) define ILEs as a combination of an ITS (that responds to individual students' actions and needs through the use of an [[student model]]) and a learning environment that allows for student-driven learning (e.g.: through the use of an [[open learner model]] where students' can view and customize their student model and learning process). | |||
Wenger (1987) points out three types of knowledge important to intelligent tutoring, and by extension also crucial to an effective ILE: | |||
* knowledge about domain | |||
* knowledge about tutoring | |||
* knowledge about the student and [[student model]] | |||
See also [[intelligent tutoring system]]s, [[artificial intelligence and education]], [[adaptive hypertext]], [[computer-supported collaborative learning]] | |||
==References== | ==References== | ||
* Brusilovsky, P. (2004). Student model centered architecture for intelligent learning environments. In Proc. of Fourth international conference on User Modeling, 15-19 August, Hyannis, MA, USA. User Modeling Inc, 1994. 31-36 | |||
* Dillenbourg. P., Hilario, M., Mendelsohn, B. Schneider, D., Borcic, B. Report from the project "Les systèmes explorateurs intelligents". Intelligent Learning Environments . FP23 Program; Project No. 4023-2701 [http://tecfa.unige.ch/tecfa/research/memolab/report93-title.html] | |||
* Kay, J. (1997). Learner Know Thyself: Student Models to Give Learner Control and Responsibility, in Z. Halim, T. Ottomann & Z. Razak (eds), Proceedings of International Conference on Computers in Education, Association for the Advancement of Computing in Education (AACE), 17-24. | |||
* Wenger, E. (1987). Artificial intelligence and tutoring systems. Computational approaches to the communication of knowledge. Los Altos: Morgan Kaufmann. | |||
[[Category: Artificial intelligence]] | |||
[[Category: Artificial intelligence and education]] | |||
Latest revision as of 17:56, 9 July 2009
Definition
Intelligent learning environments are based on various combinations of principles from microworlds, intelligent tutoring systems, cognitive tools and CSCL.
Dillenbourg et al. ([1]) offer this definition
The term `intelligent learning environment' (ILE) refers to a category of educational software in which the learner is `put' into a problem solving situation. A learning environment is quite different from traditional courseware based on a sequence of questions, answers and feedback. The best known example of a learning environment is a flight simulator: the learner does not answer questions about how to pilot an aircraft, he learns how to behave like a "real" pilot in a rich flying context...
In summary, we use the word `intelligent learning environment' for learning environments which include
- a problem solving situation and
- one or more agents that assist the learner in his task and monitor his learning.
Other views (Brusilovsky, 2004, Kay, 1997) define ILEs as a combination of an ITS (that responds to individual students' actions and needs through the use of an student model) and a learning environment that allows for student-driven learning (e.g.: through the use of an open learner model where students' can view and customize their student model and learning process).
Wenger (1987) points out three types of knowledge important to intelligent tutoring, and by extension also crucial to an effective ILE:
- knowledge about domain
- knowledge about tutoring
- knowledge about the student and student model
See also intelligent tutoring systems, artificial intelligence and education, adaptive hypertext, computer-supported collaborative learning
References
- Brusilovsky, P. (2004). Student model centered architecture for intelligent learning environments. In Proc. of Fourth international conference on User Modeling, 15-19 August, Hyannis, MA, USA. User Modeling Inc, 1994. 31-36
- Dillenbourg. P., Hilario, M., Mendelsohn, B. Schneider, D., Borcic, B. Report from the project "Les systèmes explorateurs intelligents". Intelligent Learning Environments . FP23 Program; Project No. 4023-2701 [2]
- Kay, J. (1997). Learner Know Thyself: Student Models to Give Learner Control and Responsibility, in Z. Halim, T. Ottomann & Z. Razak (eds), Proceedings of International Conference on Computers in Education, Association for the Advancement of Computing in Education (AACE), 17-24.
- Wenger, E. (1987). Artificial intelligence and tutoring systems. Computational approaches to the communication of knowledge. Los Altos: Morgan Kaufmann.